import argparse
import warnings

import sklearn.exceptions

# from test2 import test2
# from trainer import trainer
# from trainer1 import trainer1
from trainer2 import trainer2

warnings.filterwarnings("ignore", category=sklearn.exceptions.UndefinedMetricWarning)

parser = argparse.ArgumentParser()

# ========  Experiments Name ================
parser.add_argument('--save_dir', default='experiments_logs', type=str, help='Directory containing all experiments')
parser.add_argument('--experiment_description', default='Brn', type=str, help='experiment name')
parser.add_argument('--run_description', default='lightx3Ecg-268', type=str, help='run name')

# ========= Select the DATASET ==============
parser.add_argument('--dataset', default='mit4', type=str, help='mit4, ptb')
parser.add_argument('--dataType', default='brn', type=str, help='brn, brj')
parser.add_argument('--dataPath', default='data/mit/alldata/data_4.csv', type=str, help='data/mit/alldata/data_4.csv')
parser.add_argument('--seed_id', default=0, type=int, help='to fix a seed while training')

# ========= Experiment settings ===============
parser.add_argument('--data_path', default=r'data', type=str, help='Path containing dataset')

parser.add_argument('--num_runs', default=1, type=int, help='Number of consecutive run with different seeds')
parser.add_argument('--device', default='cuda:0', type=str, help='cpu or cuda')

args = parser.parse_args()

if __name__ == "__main__":
    trainer = trainer2(args)
    trainer.train()
